# OR set the environment variable globally in your shell:
export HERMETIC_PYTHON_VERSION=3.12
```

You may run builds and tests against different versions of Python sequentially
on the same machine by simply switching the value of `HERMETIC_PYTHON_VERSION`
between the runs. All the python-agnostic parts of the build cache from the
previous build will be preserved and reused for the subsequent builds.

 * adding new conversion rules, setting the entire conversion map, and converting
 * URLs using these rules.</p>
 *
 * <p>The conversion is performed by iterating through the conversion map and applying
 * each replacement rule sequentially. The order of the rules in the map is preserved
 * during the conversion process.</p>
 *
 * <p>Example usage:</p>
 *
 * <pre>{@code
 * UrlConvertHelper helper = new UrlConvertHelper();

   * Different orderings for combining the elements of an input array, which must all produce the
   * same result.
   */
  enum CollectStrategy {
    /** Get one accumulator and accumulate the elements into it sequentially. */
    SEQUENTIAL {
      @Override
      final <T extends @Nullable Object, A extends @Nullable Object, R extends @Nullable Object>
          A result(Collector<T, A, R> collector, Iterable<T> inputs) {

   * same result.
   */
  @IgnoreJRERequirement // *should* be redundant with the one on CollectorTester
  enum CollectStrategy {
    /** Get one accumulator and accumulate the elements into it sequentially. */
    SEQUENTIAL {
      @Override
      final <T extends @Nullable Object, A extends @Nullable Object, R extends @Nullable Object>
          A result(Collector<T, A, R> collector, Iterable<T> inputs) {

   *     a unique integer (0, 1, etc.) will be supplied as the single parameter. This integer will
   *     be unique to the built instance of the ThreadFactory and will be assigned sequentially. For
   *     example, {@code "rpc-pool-%d"} will generate thread names like {@code "rpc-pool-0"}, {@code
   *     "rpc-pool-1"}, {@code "rpc-pool-2"}, etc.
   * @return this for the builder pattern
   */

 * This service provides customized URL fetching strategies including sequential and random ordering
 * based on crawling configuration parameters.
 */
public class FessUrlQueueService extends OpenSearchUrlQueueService {

    private static final Logger logger = LogManager.getLogger(FessUrlQueueService.class);

    /** Configuration value for sequential URL processing order */

    @SuppressWarnings({"unchecked", "DoNotMock"})
    Funnel<Object> elementFunnel = mock(Funnel.class);
    PrimitiveSink primitiveSink = mock(PrimitiveSink.class);
    Funnel<Iterable<?>> sequential = Funnels.sequentialFunnel(elementFunnel);
    sequential.funnel(Arrays.asList("foo", "bar", "baz", "quux"), primitiveSink);
    InOrder inOrder = inOrder(elementFunnel);
    inOrder.verify(elementFunnel).funnel("foo", primitiveSink);

   *   {@code List<ListenableFuture<T>> futures = (List) executor.invokeAll(tasks);}
   * </pre>
   *
   * @return A list of {@code ListenableFuture} instances representing the tasks, in the same
   *     sequential order as produced by the iterator for the given task list, each of which has
   *     completed.
   * @throws RejectedExecutionException {@inheritDoc}
   * @throws NullPointerException if any task is null
   */
  @Override

 * decide not to by returning -1L.
 *
 * Task Queues
 * -----------
 *
 * Tasks are bound to the [TaskQueue] they are scheduled in. Each queue is sequential and the tasks
 * within it never execute concurrently. It is an error to use a task in multiple queues.
 */
abstract class Task(
  val name: String,
  val cancelable: Boolean = true,
) {

If you have traditional spinning (hdd) drives, some applications with high concurrency might require MinIO cluster to be tuned such that to avoid random I/O on the drives. The way to convert high concurrent I/O into a sequential I/O is by reducing the number of concurrent operations allowed per cluster. This allows MinIO cluster to be operationally resilient to such workloads, while also making sure the drives are at optimal efficiency and responsive.